Text Messaging/SMS

April 24, 2012

Holly Logan, M.A., iN Touch Project Coordinator, San Francisco State University

During the first cohort, we came across many challenges; some we had anticipated and others surprised us. These learnings allowed us to refine our design and conduct a second cohort. For the second cohort, each participant started out with health coaching only for two months, then received an iPod Touch, and coaching plus TheCarrot’s customized iN Touch application for two months. The refinements addressed the three major challenges faced by the first cohort: 1) Access to Wi-Fi, 2) Coaching protocol, and 3) Staying in contact with the participants.

Many participants told us that the number one reason they had problems with recording their ODLs was because they did not have Wi-Fi at home and did not know where to access it. Although we had installed a Free Wi-Fi Finder app on their iPods, it still seemed that the participants faced a major obstacle when it came to finding Wi-Fi to record their ODLs. To address this issue, we asked Mission High School for permission to give the participants the Wi-Fi password at school. They agreed, so during the iPod provisioning, we entered the password into each device and informed the participants that they could record their ODLs during lunch and after school. This has been working well for the new cohort.

The second challenge was the initial health coach protocol we had created, which detailed how the health coach should direct participants about what to record, when to record, etc. For the first cohort, we sent reminders to ask participants to record, but we didn’t have a set schedule of what we wanted them to do on a weekly basis. For the second cohort, we developed a Health Coach Guide that the health coach was to follow each week when meeting with the participants. This included setting goals, asking participants to record, checking in through text messages and updating the health coaching logs as well as measurements at each visit. This has helped keep the coach and participants better engaged through each step.

Finally, communicating with the patients and scheduling them to come down during school hours was an issue with the first cohort. We had been using a texting application called Text4Plus, but a lot of the participants were not getting our texts. We had no way to know if they had received our messages or not. For the second cohort, we updated all of the iPods by installing iMessage, and sent and received messages through that application. iMessage allowed us to verify whether a message had been delivered. If it did not say ‘delivered,’ we knew to send it again until it was delivered. This has helped us stay in better contact with the second cohort, and we have been able to easily let them know when we have sent a pass for them to come see us during school hours.

We are now in the third month of the new cohort, and we may still face challenges in the next two months. However, we’ve had a lot of success with giving the participants the Wi-Fi password, following a detailed protocol and keeping in contact with them through iMessage.

Our technology team has included a diverse group: a health informatics researcher/CTO, an architect, a health services researcher, and a UCB undergraduate/patient/usability specialist. Because our project experienced administrative delays and personnel setbacks during the first year of funding, the beginning of 2011 required an expedited execution of our app technology. With four people and four very different levels of expertise in the various disciplines required to develop a mobile health app, the effort has been fun, challenging and occasionally frustrating, but ultimately rewarding and educational.

We developed two apps for this study: the Chronology.MD app that allows patient participants to enter data on an iPhone/iPad/iPod, or via SMS text message on other types of phones; and the Crohnograph app, which provides visualizations of the patient data in trend line form on the iPad.

Some challenges we addressed include:

Multiple technology partnersIn addition to Apple devices, each patient also received a Withings Body Mass Scale and a Fitbit activity monitor that are used to collect ODL data (e.g., weight, steps taken, sleep) . We brought in technology partners, including iMedic8 (the medication adherence app upon which we built our platform), so that we didn’t have to reinvent the wheel. Working with iMedic8, Withings and Fitbit brought us great capabilities but meant coding our apps to conform to all of these existing platforms.

Multiple authentication methods Similarly, the authentication processes for Withings and Fitbit were different. One supports direct back-end authentication while the other requires the user to navigate to their site on the device to authenticate. To make this happen, our developer needed to adapt around the existing workflow of these two technology partners.

OS upgrades We confronted the realities of dealing with Apple OS upgrades. Because an upgrade occurred mid-project, our app needed to work with Apple OS4 as well as the newer OS5.

Hardware variations We had to work with multiple types of hardware, and we had to find ways for the app to work with multiple configurations such as the iPad and SMS text messaging.

Patient data integration Our plan for patient data integration was thwarted when Google Health (our planned data repository) was discontinued. Changes happen. Even large, stable companies cancel products, and we have had to adapt to this reality.

Performance issues Although our design team had outstanding ideas about data visualization (e.g., screen pinch and zoom timelines for data), some of those ideas were beyond the reality of processor/computing capacity at this time.

Vendor issues Apple hardware is elegant, but we did have challenges working with Apple, including a very limited discount for nonprofits and research projects, as well as having to go through their application review process with a limit of only 100 provisions for testing.

Technology successes we can identify at this point include:

We predicted that participants would want to use their own phones for the project, which turned out to be the right call. Not everyone wants to give up their plain old cell phone for a smartphone. In order to accommodate these users, we incorporated SMS text messaging into the app, and all patient participants received iPads that can be used for both ODL data collection and data visualization.

The popularity of the iPad and the other devices we offered to the cohort have resulted in great user compliance and lots of enthusiasm for the project.

We have been able to integrate data via the effective APIs available from Withings and Fitbit.

The device makers realized that multiple people in a household will use the Withings scale, and the log in allows additional names and tracking capabilities. Similarly, iMedic8 can handle additional users.

July 12, 2011

In the past 10 years, there’s been a huge increase in the use of cell phones (particularly smartphones); social media, including Twitter, Facebook and blogs; networking tools; and information sharing systems, including mobile geolocation applications such as Foursquare. These tools may offer new opportunities for enhancing techniques and processes for collecting health data, including participant recruitment; tracing; maintaining contact with participants in longitudinal studies; cognitive interviewing; and passive data collection.

Text messaging is one of the most popular communication methods in the world. The pervasiveness, low cost and convenience of mobile phones make Short Message Service (SMS) texting an ideal tool for disseminating health information to—as well as gathering health information from—consumers. It’s also a direct and immediate route to reach people; I tend to think of it as the most intimate form of high-tech communication.

Despite these advantages, rigorous evaluations of new technologies in health services research applications have been rare. The few SMS interventions that have been well-studied suggest that text messaging systems can effectively increase medication and appointment adherence and sustain health promotion behaviors such as smoking cessation, diabetes, asthma management and depression.

I’ve been so enamored of texting and its potential over the past couple of years that I decided to build an SMS platform for sending and receiving messages for health behavior change interventions. After reflecting on these trends and considering how we can make the BreathEasy smartphone experience more engaging, we hit on the idea of integrating SMS notifications with the application.

So that’s where we are now: devising and testing methods to tie our SQL back end from the BreathEasy application side to the SMS platform in order to generate three kinds of messages. The first type of tailored reminder prompts participants to complete diary entries and/or provide peak flow readings; the second involves health alerts related to air quality, excessive use of rescue inhalers and peak flow readings; the third type of messages are health promotion messages that address general wellness and smoking cessation.

For BreathEasy, rather than focusing on text messaging as a mode of intervention or primary collection of observations of daily living (ODLs), we decided to try using SMS as an adjunctive technology. Our SMS-adjunct (SMS-a), is intended to support the collection of ODLs; SMS-a provides participants interactive, dynamically tailored compliance reminders via a smartphone application. Beyond serving as a technical and process proof of concept, we intend to evaluate the effect of SMS-a on increasing participant satisfaction, retention and data quality.

We’re eager to get started with ODL collection and even more excited to observe how things go with this integration. We’ll be sure to update you about our experience when we go live.